1. Field of the Invention
The invention relates in general to a system for use in optimizing mobility management in a wireless communication system and the method thereof, and more particularly to a system for constructing a mobility model for use in optimizing mobility management in a wireless communication system and the method thereof.
2. Description of the Related Art
In order to satisfy the convenience, efficiency requirement of the modern people, wireless communication systems have been developed rapidly. All kinds of wireless communication devices, such as cell phones or mobile stations, are widely used in the world.
FIG. 1 shows the rough architecture of a sample wireless communication network. Using a cellular system as an example, the geographical coverage area of the wireless communication system is partitioned into cells, served by base stations. Each mobile station of an individual subscriber is connected to the wireless network via the base stations. The coverage of cells differs greatly according to various factors, such as the power of the base station, the geographical features (e.g. mountains, valleys, rivers) within the cells, the area (e.g. city, suburb) of the cells, the architecture (e.g. tall buildings, railroad, highway) within the cells, etc. One or more cells are respectively combined to a location area (LA), also known as Paging Area, Routing Area, or Registration Area in some systems. Basically, a location area is a region in which subscribers can move arbitrarily without requiring a location area update, which incurs central database update (e.g. in a Home Location Register or Visitor Location Register) of the location area information that is utilized for describing the current location area of subscribers. The size of a location area is defined to cover the demands raised by traffic density and flow, population density and subscriber mobility, etc.
Mobility management enables the wireless network to find the locations of mobile stations so as to deliver incoming calls, messages, or packets to mobile stations. Mobility management includes location update, paging, and other operations, such as handover, that are related to the location or mobility of subscribers. Since subscribers are free to move within the service area of the system, the system can only maintain the approximate location of each subscriber. When a connection needs to be established for a particular subscriber, the system has to determine the subscriber's exact location, to the accuracy of a cell, within the location area. When a subscriber leaves the border of the specific location area, the mobile station must register its new location area through signaling the location area information to the system. This procedure is called updating (location area update), or location registration. The updating procedure is for informing the system about the current location area of the subscriber. Besides location area update, there are also other types of location update that will be described later in this specification. When the system tries to deliver a phone call or message to a subscriber by first finding the location of the specific subscriber, the system can search among the cells within the current location area of the mobile station. This procedure is called paging. The paging procedure is for determining the exact location, to the accuracy of a cell, of the subscriber.
Because there are many tradeoffs and high complexity involved, the parameters involved in mobility management are difficult to define in an optimal manner. For example, how to define the scope, including size and the border cells, of location areas so as to decrease the overall cost of the wireless communication system is an important issues for optimizing mobility management. Since a location area is composed of cells, the size and the border of each location area can be defined by deciding which cells are collected into the location area. If the size of the location area is too small, mobile stations cross the location area frequently. As a result, the mobile stations perform location area update frequently and the location accuracy is to a smaller region, the system can thus have lower paging load. However, the system must waste its resources by performing frequent location area update, and the mobile station must waste its power transmitting the location area update signal. On the other hand, if the size of the location area is too large, mobile stations cross the border of the location areas rarely and do not perform location area update frequently. However, a large coverage area has to be paged when a call or a message arrives, which waste resource of the system. In addition, the border of the location area is also an important factor in defining the scope of the location area. If the border of the location area is set parallel to and close to major highways, or in heavy traffic regions where population and mobility behavior of the subscribers are high, the subscribers may result in much location area update. Furthermore, the subscribers may cross the border of a specific location area back and forth, thereby causing much location area update, if the border of the location area is not properly set. As a result, the system wastes its resources by processing frequent location area update procedure, and the mobile stations waste power transmitting the location area update signal.
Various conventional mobility models, such as fluid flow model, gravity mode, random walk model, etc, are presented as a basis for studying issues resulted from subscribers' behavior. For further discussion, please refer to “Location Management for Next-Generation Personal Communications Networks” (pp. 18˜pp. 24, IEEE Network, September/October 2000) incorporated herein by reference. Those conventional mobility models are more used for studying issues resulted from subscribers' behavior, than optimizing mobility management for a live wireless communication system. They lack enough precision and accuracy to practically optimize mobility management due to the following reasons.
First, each of these conventional models is based on certain intuitions and assumptions and might not correctly model realistic use of a live system. Taking the fluid flow model as an example, the fluid flow model is used for simulating the aggregate mobility behavior of the fluid in the flow or any other systems which the aggregate mobility behavior of the components in the system is like the fluid in the flow. It is obvious that the feature of the fluid flow is different from the subscribers of the wireless communication system in a crowded city. Therefore, the fitness of applying fluid flow model to model the aggregate mobility behavior of the subscribers in a crowded city is questionable. In the same manner, the fitness of other conventional mobility models is questionable for widespread use in optimizing mobility management in a live wireless communication system, since the real model is usually different from a hypothetical one.
Second, since the subscribers' mobility behavior in a wireless communication system is complicated, some of the conventional mobility models are oversimplified that they only specifically put stress on certain factors and significantly simplify the complexity of the mobility behavior of the subscribers. Therefore, those conventional mobility models lack enough accuracy to reflect the real mobility behavior of subscribers for optimization mobility management.
Third, since data of real wireless communication systems are difficult to acquire, most of the conventional mobility models are proposed or built upon simulated data, not a plurality of data obtained from real wireless communication systems. Due to the above-described reasons, the reliance and the accuracy of the simulation result of those mobility models are questionable if they are applied to optimizing mobility management.
In the present time, there is no optimal method or algorithm which is proven to be able to minimize the overall cost of mobility management based on realistic mobility model of subscribers. From time to time, mobility management parameters need to be redefined. For example, from time to time the scope of location area needs to be redefined, such as splitting it into two new location areas when equipment of the old location area reaches its paging capacity. In practice, mobility management parameters are defined according to the subjective experience and rough judgment of the wireless operators. It is obvious that this kind of methods have difficulty minimizing the overall cost of mobility management. Although there are optimization algorithms that can be used, as will be introduced and incorporated later in this specification, without a realistic mobility model their practicability and accuracy are highly limited. The conventional approaches either has difficulty to find the optimal strategy out of numerous possible configurations, or do not concisely take into account the mobility characteristics of the entire system. This results in extra or unbalanced resource consumption, and leads operators to more capital expenditure on hardware expansion as mobility management traffic grows.